Michael Vácha1,2,3, Frank Hofheinz1, Anja Braune1,4,5, Steffen Löck2,3,6,7,8, Alex Zwanenburg3,7,8
1Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
2Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany
3OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
4Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
5Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
6Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
7German Cancer Consortium, partner site Dresden, and German Cancer Research Center, Heidelberg, Germany
8National Center for Tumor Diseases (NCT), NCT/UCC Dresden, Dresden, Germany
There is an increasing interest in using positron emission tomography (PET) data for segmentation, biomarker identification, and outcome prediction. To make PET values comparable between patients, these values are often normalized to a standard unit, which is, in most cases, the body-weight-normalized standardized uptake value (SUVbw). By definition, the SUVbw can be computed from the formula:
\[ \text{SUV}_{\mathrm{bw}} = \frac{\scriptstyle A_c \, W}{\scriptstyle D} \]
where \({A}_{c}\) represents the measured activity concentration within a region of interest or voxel in Bq/ml, \(W\) the weight of the patient in g, and \(D\) the total administered radionuclide dose at the time to which the voxel values correspond, in Bq. However, PET imaging data in Digital Imaging and Communications in Medicine (DICOM) files are usually not stored as standardized uptake values. Consequently, the voxel values and associated metadata have to be correctly interpreted by the viewing or analytical tools in order to convert the image units to SUVbw. In the radiomics field, many tools were not primarily designed for PET imaging and may not process all relevant metadata correctly. Consequently, identical images may be processed inconsistently across various software tools. This can give rise to two potential issues:
By creating reference standards for SUVbw computation by software tools, we aim to:
Therefore, we:
To analyze how PET imaging data are stored, we searched for real-world PET human imaging series via two sources:
We identified 37 cohorts containing relevant PET imaging data: ACRIN-FLT-Breast, ACRIN-NSCLC-FDG-PET, Anti-PD-1_Lung, BREAST-DIAGNOSIS, CC-Tumor-Heterogeneity, CMB-CRC, CMB-GEC, CMB-LCA, CMB-MEL, CMB-MML, CMB-PCA, CPTAC-CM, CPTAC-HNSCC, CPTAC-LSCC, CPTAC-LUAD, CPTAC-PDA, CPTAC-SAR, CPTAC-UCEC, CT-vs-PET-Ventilation-Imaging, Head-Neck-PET-CT, Internal-Berlin, Internal-Dresden, Internal-Munich, Lung-PET-CT-Dx, NaF PROSTATE, NSCLC Radiogenomics, QIN-BREAST, RIDER Lung PET-CT, Soft-tissue-Sarcoma, TCGA-BLCA, TCGA-KIRP, TCGA-LUAD, TCGA-LUSC, TCGA-PRAD, TCGA-THCA, TCGA-UCEC, and VAREPOP-APOLLO.
We excluded imaging series without attenuation correction and detector normalization applied, as well as maximum intensity projections and other reprojections. For all remaining series, we scanned a preselected set of attributes (listed in Suppl. Table 1) and analyzed how they were used in practice.
Based on literature (DICOM standards, QIBA consensus, Turku PET center manual), our expertise, and the metadata analysis, we summarized the rules for converting PET images into SUVbw-normalized images.
Furthermore, we assembled a comprehensive set of digital reference objects (DROs) for verifying SUV conversion. All DRO DICOM files were synthesized de novo using Python pydicom library version 3.0.1. The design of these DROs was chosen to resemble common PET calibration phantoms – each DRO includes one hot sphere (SUVbw = 4.00), one cold sphere (SUVbw = 0.20), a background region (SUVbw = 1.00), and surrounding zero-activity region (SUVbw = 0.00) (See Fig. 1).
All DROs are identical in terms of the design, volumes, and resulting SUVbw values, while the stored voxel values and DICOM attributes vary based on the intended use of each DRO. The binary mask for feature extraction covers the whole DRO volume, excluding the surrounding region. To verify a software tool computes the SUVbw correctly, either:
convert the DRO DICOM file to SUVbw and extract the DRO maximum, minimum, and median SUVbw values from the region defined by the mask, or
convert the DRO DICOM file to SUVbw and visually inspect the values in the hot sphere, cold sphere, and background region.
All values should be calculated with a precision of two decimal digits. The target values are identical across all cases and are defined as follows:
Fig. 1: Visualization of the DRO design in axial, coronal, and sagittal planes (from left to right). Voxel values are shown in SUVbw.
For the metadata analysis, we identified and examined 3433 PET imaging series from 1775 patients. These images were acquired by a large variety of PET scanner models constructed by 3 major PET scanner manufacturers (See Table 1).
| Manufacturer | Perc | Models |
|---|---|---|
| GE | 59% | Advance, Discovery 610, Discovery 690, Discovery 710, Discovery IQ, Discovery LS, Discovery MI, Discovery MI DR, Discovery RX, Discovery ST, Discovery STE |
| Philips | 11% | Allegro Body(C), GEMINI TF Big Bore, GEMINI TF TOF 16, Guardian Body(C), TruFlight Select |
| Siemens/CTI/CPS | 29% | 1023, 1024, 1062, 1080, 1093, 1094, 962, Biograph 20_mCT, Biograph 64_mCT, Biograph Horizon, Biograph_mMR, Biograph128_mCT 4R, Biograph128_Vision 450 Edge, Biograph16_Horizon 3R, Biograph20_mCT, Biograph20_mCT 3R, Biograph40_mCT, Biograph40_mCT 4R, Biograph40_TruePoint, Biograph6_TruePoint, Biograph64_mCT, Biograph64_mCT 3R, Biograph64_Vision 600, Somaris/5 3D, Somaris/5 3D Postprocessing, SOMATOM Definition AS_mCT |
| Unknown | 1% | DicomCleaner, Integrity Medical Image Importer |
Because of the wide range of the measured voxel values in PET imaging data, the use of rescale slope (RescaleSlope; 0028,1053) ensures that stored values are within the range that can be stored in the voxel data type (e.g., signed 16-bit integers can store integer values from -32,768 to 32,767). Applying the rescale slope to the stored voxel data is the mandatory first step in SUV calculation, independent of the units encoded in the DICOM image:
\[ \text{SUV}_{bw} = \frac{\scriptstyle(m \, P + b)\, W}{\scriptstyle D} \]
where P is the stored voxel value (PixelData; 7fe0,0010) in Bq/ml, m the rescale slope, b the rescale intercept (RescaleIntercept; 0028,1052). The rescale slope may vary for each slice and must be applied on a slice-wise basis. Since the rescale intercept is required to be 0 in all PET studies, it can be omitted from the formula:
\[ \text{SUV}_{bw} = \frac{\scriptstyle m \, P \, W}{\scriptstyle D} \]
Comparing series, a wide range of rescale slopes was observed in the studied data.
In general, the rescale slope values within each series were either (see Table 2):
| N unique RescaleSlope values | Freq | Perc |
|---|---|---|
| = 1 | 1342 | 39 % |
| 1 < N_Slices | 391 | 11 % |
| = N_Slices | 1698 | 49 % |
In our dataset, all PET imaging series had RescaleIntercept = 0.
The following DRO was constructed:
DRO with multiple values of the RescaleSlope attribute.
Possible issues:
RescaleIntercept (0028,1052) attribute should be checked to ensure it equals 0. Otherwise, exclude the dataset.
The corresponding RescaleSlope (0028,1053) has to be applied to all stored voxel values within a slice, independently of other parameters such as the units.
The attribute PixelData (7fe0,0010) stores the voxel values. As for other imaging modalities, the PixelData attribute can be read using other attributes from the DICOM Image Pixel Module, such as Rows (0028,0010), Columns (0028,0011), Bits Allocated (0028,0100), or Pixel Representation (0028,0103). While single-slice DICOM images still prevail, multi-planar DICOM images containing 3-D voxel data (i.e., ‘one-file DICOM’ formats) may become increasingly common in the future. For PET imaging, the interpretation of these values depends on the unit specified in the Units (0054,1001) attribute, which is explained in the following subsections.
Voxel values are commonly in becquerels per milliliter: the attribute Units (0054,1001) is set to “BQML”. Assuming W and D are accordingly corrected and expressed in proper units, P may be used directly in the formula:
\[ \text{SUV}_{\mathrm{bw}} = \frac{\scriptstyle m \, P \, W}{\scriptstyle D} \]
However, other units may be used by scanners or due to previous processing of the DICOM file.
The voxel values can be in grams per milliliter (Units = GML). This indicates the activity concentration was already normalized. In most cases, the normalization corresponds to body-weight normalization (BW), where the SUV voxel value equals the stored value multiplied by the rescale slope.
\[ \text{SUV}_{bw} = m \, P \]
However, there may be scenarios where other normalization techniques were applied. Specifically, four SUV methods are compliant with the current DICOM standard and result in the unit GML. The method used can be extracted from the attribute SUVType (0054,1006) and should be considered as BW if empty. The following factors are used, as reported by Sugawara:
lean body mass by Morgan (SUVType = “LBM”)
for male patients: \(\text{LBM} = 1.10 W - 120 ({\scriptstyle \frac{W}{H}})^2\)
for female patients: \(\text{LBM} = 1.07 W - 148 ({\scriptstyle \frac{W}{H}})^2\)
lean body mass by James et al. (James, William Philip Trehearne, and J. C. Waterlow. Research on obesity. 1976) / Morgan (SUVType = “LBMJAMES128”)
for male patients: \(\text{LBM} = 1.10 W - 128 ({\scriptstyle \frac{W}{H}})^2\)
for female patients: \(\text{LBM} = 1.07 W - 148 ({\scriptstyle \frac{W}{H}})^2\)
lean body mass by Janmahasatian (SUVType = “LBMJANMA”)
\(\text{BMI} = \scriptstyle \frac{W}{H^2}\)
for male patients: \(\text{LBM} = \scriptstyle \frac{ 9270 W}{6680 + 216 \text{BMI}}\)
for female patients: \(\text{LBM} = \scriptstyle \frac{9270 W}{8780 + 244 \text{BMI}}\)
ideal body weight (SUVType = “IBW”)
for male patients: \(\text{IBW} = 48.0 + 1.06 (H - 152)\)
for female patients: \(\text{IBW} = 45.5 + 0.91 (H - 152)\)
For all formulas, W is weight in kg, and H is height in cm. Additionally, the following attributes are required:
PatientSize (0010,1020) - Height of the patient in m
PatientSex (0010,0040) - Sex of the patient - M (male), F (female) or O (other)
In turn, these factors can be used for the normalization, e.g., for SUVlbm:
\[ \text{SUV}_{\mathrm{lbm}} = \frac{\scriptstyle A_c \, \text{LBM} \, 10^{3}}{\scriptstyle D} \]
To get the SUVbw values, the stored voxel values can be divided by the corresponding factor and multiplied by the patient’s weight and the rescale slope of the slice, e.g., for LBM:
\[ \text{SUV}_{bw} = \frac{\scriptstyle m \, P \, W}{\scriptstyle \text{LBM} \, 10^{3}} \]
There is currently no consensus on the computation of LBM and IBW when PatientSex is specified as “O”. Using the mean value of the sex-specific factors appears to be a reasonable and simple solution.
The unit square centimeters per milliliter (Units=“CM2ML”) corresponds to images normalized to body surface area (BSA) using the Du Bois formula:
\[ \text{BSA} = 0.007184 \, H^{0.725} \, W^{0.425} \]
where H is height in cm, and W is weight in kg. The SUVType (0054,1006) should be set to “BSA” in this case. SUVbw can be backcomputed analogically to the previous section:
\[ \text{SUV}_{bw} = \frac{\scriptstyle m\, P \, W}{\scriptstyle \text{BSA} \, 10^{4}} \]
Philips scanners often save voxel values as counts (Units=“CNTS”). In this case, scale factors may be provided for converting the stored values to activity concentration or directly to SUV values. SUV scale factor allows direct conversion of the voxel values to SUVbw. The formula is mentioned in Philips conformance statements (here, for Philips Ingenuity):
(7053,1000) DS SUV Scale Factor: This value only applies when Units (0054,1001) is equal to CNTS. The SUV Scale Factor is used to convert the voxel data from counts to an SUV value. This is done by using the formula SUV Value = ((SV x m) + b) x f, where: SV = original stored voxel value, m = Rescale Slope (0028,1053), b = Rescale Intercept (0028,1052), f = SUV Scale Factor (7053, 1000). If the SUV Scale Factor is 0.0, then the voxel data cannot be converted from counts to an SUV value.
The Activity Concentration Scale Factor allows the conversion of the voxel values to Bq/ml, as explained in the conformance statement (here, for Philips Ingenuity):
(7053,1009) DS Activity Concentration Scale Factor: This value only applies when Units (0054,1001) is equal to CNTS. The Activity Concentration Scale Factor is used to convert the voxel data from counts to Activity Concentration (in Bq/ml). This is done by using the formula Activity Concentration Value = ((SV x m) + b) x f, where: SV = original stored voxel value, m = Rescale Slope (0028,1053), b = Rescale Intercept, (0028,1052), f = Activity Concentration Scale Factor (7053, 1009). If the Activity Concentration Scale Factor is 0.0, then the voxel data cannot be converted from counts to Activity Concentration.
In case none of the factors is provided, counts (CNTS) can be converted to counts per second (CPS) by dividing by the actual frame duration in seconds, i.e., the Actual Frame Duration attribute (0018,1242) value divided by 1000.
Counts per second (CPS) can be converted to activity concentration (Bq/ml) based on whether the image is dose calibrated or not, which can be derived from the presence of “DCAL” in the attribute Corrected Image (0028,0051):
The dose calibration factor is stored in the corresponding DICOM attribute Dose Calibration Factor (0054,1322). However, in most cases, the factor may be unknown. The voxel volume can be computed from the Pixel Spacing (0028,0030) and Slice Thickness (0018,0050) attributes, that show the dimensions of a single voxel in mm.
Furthermore, it must be verified that all required image corrections have been applied, as this unit is often associated with uncorrected image data.
For other units, the conversion to activity concentration or SUVbw is impossible or unclear.
That includes, above all, following units:
PROPCNTS - proportional to counts, not mentioned in conformance statements, conversion is not clear
PROPCPS - proportional to counts per second, mentioned by Siemens for “non-quantitative, non-attenuation corrected images”, conversion is not clear
1CM - 1/centimeter, used for MU maps
The units used were highly dependent on scanner manufacturer (see Table 3):
| BQML | CNTS | CPS | GML | PROPCNTS | |
|---|---|---|---|---|---|
| Total | 2987 | 248 | 121 | 44 | 33 |
| GE | 1839 | 0 | 121 | 34 | 33 |
| Siemens/CTI/CPS | 1000 | 0 | 0 | 0 | 0 |
| Philips | 113 | 248 | 0 | 10 | 0 |
| Unknown | 35 | 0 | 0 | 0 | 0 |
There were no cases with a non-NA value in the SUVType attribute.
Regarding counts as units and their conversion, 90% of the series with counts units had at least one scale factor provided, of which the SUV scale factor appeared most often. The activity concentration scale factor never appeared without the SUV scale factor (See Table 4).
| ACSF | SUVSF | Freq | Perc |
|---|---|---|---|
| TRUE | TRUE | 136 | 55 % |
| FALSE | TRUE | 87 | 35 % |
| FALSE | FALSE | 25 | 10 % |
| TRUE | FALSE | 0 | 0 % |
We synthesized multiple DROs verifying a standardized conversion to SUVbw:
DRO with Units = BQML and Decay Correction = START (baseline DRO)
Possible issues:
DRO Units = GML (corresponding to SUVbw)
Possible issues:
unit GML is not implemented;
SUVtype is required (while should be considered “BW” by default);
RescaleSlope is not applied;
other corrections are applied.
DRO Units = GML (corresponding to SUV LBMJAMES128)
Possible issues (not considering previously mentioned):
SUVlbm is not implemented;
incorrect formula for LBM is used (instead of LBMJAMES128 DICOM standard);
LBM unit is not changed to g;
patient’s weight, height or sex are not extracted correctly;
SUV type is not extracted correctly.
DRO PatientSex = “O” (other) with Units = GML (corresponding to SUV IBW)
Possible issues (not considering previously mentioned):
SUVibw is not implemented;
strategy for PatientSex = “O” is not implemented.
DRO Units = CM2ML (corresponding to SUVbsa)
Possible issues (not considering previously mentioned):
SUVbsa is not implemented;
incorrect formula for BSA is used;
BSA unit is not changed to cm2.
DRO Units = CNTS using Philips SUV scale factor
Possible issues (not considering previously mentioned):
unit CNTS is not implemented;
SUV scale factor is not extracted or applied correctly.
DRO Units = CNTS using Philips activity scale factor
Possible issues (not considering previously mentioned):
tbd
PatientWeight (0010,1030) is often manually entered, which can result in missing values or incorrect units. The correct DICOM unit is kilograms, which must be converted to grams for SUV computation. Values exceeding 1000 indicate that the weight was entered in grams. Furthermore, patient weight is occasionally incorrectly stored in another DICOM attribute, particularly PatientSize (0010,1020).
In our dataset, no PatientWeight values exceeded 1000. In 0.8% of cases, the value was missing.
–
PatientWeight (0010,1030) attribute should be checked that it is present and != 0. Otherwise, SUV can’t be computed.
PatientWeight (0010,1030) attribute should be checked to ensure that the value was entered in kilograms. If the value > 1000, divide by 1000.
The RadionuclideTotalDose (0018,1074) DICOM field records the total
administered dose of the radiopharmaceutical. It is another attribute
that is typically recorded manually, which may result in missing values
or incorrect units.
Furthermore, the unit may not be standardized as different Information
Object Definitions (IODs) allow either Bq or MBq. For the equation, the
unit has to be recognized by its value and converted to Bq.
For SUV conversion, the administered dose must correspond to the time at which the voxel values occurred. This requires a correction of the administered dose for radioactive decay of the radionuclide between the time of administration and the corresponding reference time point. Therefore, it is essential to know whether the images were decay-corrected and, if so, to which time point. This information is provided by the DecayCorrection (0054,1102) attribute, which can take one of three values (“ADMIN,” “START,” or “NONE”). As shown below, the subsequent correction steps depend on this attribute.
The value “ADMIN” indicates that the PET image data were decay-corrected to the time of radipharmaceutical administration. In this case, no additional correction of the administered dose is required, because it already represents the dose at the time point to which the images were decay-corrected. The formula can be written as:
\[
\mathrm{SUV}_{bw} = \frac{\scriptstyle m \, P \, W}{\scriptstyle
D_\mathrm{adm}}
\]
In most cases, the decay correction attribute is set to “START”, implying the series was decay corrected to a reference time representing the start of the PET image acquisition. The administered dose has to be adjusted to account for decay between administration and the reference time, using the formula: \(D = {D}_{adm} e^{-\lambda (t_\mathrm{ref}-t_\mathrm{adm})}\). Then, SUV can be computed using the formula:
\[ \mathrm{SUV}_{bw} = \frac{\scriptstyle m \, P \, W}{\scriptstyle D_\mathrm{adm} \, e^{\left(-\lambda (t_\mathrm{ref}-t_\mathrm{adm}) \right)}} \]
where \(D_{adm}\) the administered dose of the radionuclide (0018,1074) in Bq, \(t_{ref}\) the reference time, \(t_{adm}\) the radiopharmaceutical administration time (0018,1072). \(\lambda\) represents the decay constant for the radionuclide and is computed as \(\lambda = \frac{\ln(2)}{T_{1/2}}\) where \(T_{1/2}\) is the radionuclide half life (0018,1075).
The reference time, to which the image was corrected can be derived by multiple methods.
The Quantitative Imaging Biomarkers Alliance (QIBA) recommends the following approach (ordered by priority):
\[ \text{t}_{ref} = \text{t}_{acq} + \text{T}_{ave} - {\Delta{t}} \]
where \({t}_{acq}\) is the acquisition time, \(\Delta{t}\) is the frame reference time in seconds, and \({T}_{ave}\) is the average count rate time in seconds which is implementation-dependent. One of the common formulas is: \({T}_{ave} = \frac{1}{\lambda} \text{ln} \frac{(\lambda \text{T})}{1 - e^{-\lambda \text{T}}}\) where \(\lambda = \frac{\ln(2)}{T_{1/2}}\), \(\Delta{t}\) is the frame reference time in sec, and \(T\) is the frame duration in sec, which leads to the formula:
\[ \text{t}_{ref} = \text{t}_{acq} + \frac{1}{\scriptstyle \lambda} \text{ln} \frac{\scriptstyle (\lambda \text{T})}{\scriptstyle 1 - e^{-\lambda \text{T}}} - {\Delta{t}} \]
Ad 2) GE states in their conformance statements:
This is only stated for some models (e.g., Discovery ST/ RX/ STE) unlike some other models (e.g., Discovery 710/610 or Optima 560). Furthermore, in the 2009 response to QIBA by GE, this private attribute is mentioned to be used for dose correction in case of processed images, where SeriesTime > AcquisitionTime.
Siemens also uses a private tag as can be seen in its conformance statements:
This suggests that the GE private tag overwrites SeriesDate and SeriesTime and should therefore be preferred when present, whereas the Siemens private tag appears to be irrelevant for our purposes.
We suggest always using the method 4) – backcomputation from acquisition time, frame reference time, and frame duration. This method seems to be the most robust for research use since:
If one of the required attributes is missing, the series should be excluded from the analysis.
Another scenario involves PET images that have not been decay-corrected, with DecayCorrection set to “NONE”. In this case, more complex formulas must be applied to ensure that each image is corrected to a reference timepoint, that matches the one used for the administered dose. This is particularly challenging in multi-frame or dynamic series consisting of images with different acquisition times. To perform this correction, the voxel values must be scaled to the reference time using the factor \(e^{\lambda (t_{\text{scan}} - t_{\text{ref}})}\) where the \({t}_{scan}\) is derived from the acquisition time and the average count rate time \({t}_{scan} = {t}_{acq} + {T}_{ave}\). Using the \({T}_{ave}\) expression from the previous section, this term can be incorporated into the original equation, resulting in the following formula:
\[ \mathrm{SUV}_{bw} = \frac{ m \, P \, W }{ D_{\text{adm}} } \frac{ e^{\lambda ({t}_{acq} + \frac{1}{\lambda} \text{ln} \frac{(\lambda \, \text{T})}{1 - e^{-\lambda \text{T}}} - t_{\text{ref}})} }{ e^{\! -\lambda (t_{\text{ref}} - t_{\text{adm}})} } \]
That can be simplified to:
\[ \mathrm{SUV}_{bw} = \frac{\scriptstyle m \, P \, W}{\scriptstyle D_{\mathrm{adm}}} \frac{\scriptstyle \lambda \, T}{\scriptstyle 1 - \mathrm{e}^{-\lambda T}} \mathrm{e}^{\lambda (t_{\mathrm{acq}} - t_{\mathrm{adm}})} \]
where the SUVbw can be computed for each image directly from the values in the DICOM attributes. This method may lead to minor inaccuracies due to different implementations of the average count rate time \({T}_{ave}\) between scanner manufacturers.
After excluding non-fluorine-18 series, two distinct peaks at approximately 4 × 10² and 4 × 10⁸ suggest that the administered dose was stored in MBq or Bq, respectively (see Fig. 2):
Fig. 2: Histogram of RadionuclideTotalDose (DICOM tag 0018,1074) values for FDG-PET series.
Regarding the dose correction, most series were decay-corrected to the acquisition start time (DecayCorrection = “START”), while there were no series decay-corrected to the administration time (DecayCorrection = “ADMIN”, Table 5):
| DC | GE | Philips | Siemens/CTI/CPS | Unknown |
|---|---|---|---|---|
| START | 2022 | 279 | 1000 | 35 |
| NONE | 5 | 92 | 0 | 0 |
More than a half of the series contained multiple AcquisitionTime (0008,0032) values (Table 6):
| N unique AcquisitionTime values | Freq |
|---|---|
| = 1 | 1393 |
| 1 < N_Slices | 2040 |
| = N_Slices | 0 |
The GE scan datetime often differed from the SeriesTime (Table 7):
| SeriesTime | AcquisitionTime | |
|---|---|---|
| = private tag | 385 | 289 |
| != private tag | 128 | 224 |
| no_value | 0 | 0 |
While, the Siemens scan datetime was always identical to SeriesTime (Table 8):
| SeriesTime | AcquisitionTime | |
|---|---|---|
| = private tag | 166 | 5 |
| != private tag | 0 | 161 |
| no_value | 0 | 0 |
Following DROs for decay correction alternatives were created:
DRO dose in MBq
Possible issues (not considering previously mentioned):
DRO DC = ADMIN
Possible issues (not considering previously mentioned):
DRO DC = START but SeriesTime after AcquisitionTime (DC = START, option 4)
Possible issues (not considering previously mentioned):
SeriesTime is not compared with AcquisitionTime;
the reference time formula is not implemented;
administered dose is not corrected to the same reference time among frames.
DRO GE private DC datetime (DC = START, option 2)
Possible issues (not considering previously mentioned):
DRO DC = NONE + multiple values ACQ TIME
Possible issues (not considering previously mentioned):
DecayCorrection == NONE is not implemented;
AcquisitionTime and FrameDuration are not extracted correctly;
wrong formula for voxel value decay correction and dose correction is used;
the voxel values and the administered dose are not corrected to the same timepoint.
tbd
Originally, radiotracer administration time was stored in the DICOM tag RadiopharmaceuticalStartTime (0018,1072). However, this attribute lacks the information about the date, therefore, was deprecated and Radiopharmaceutical Start DateTime (0018,1078) should be used instead.
Among the examined data, 59 % of series included only the RadiopharmaceuticalStartTime without an associated date, 35 % included both values, and 6 % included neither (Table 9). There was only 1 case in which only RadiopharmaceuticalStartDateTime was present, which may be due to the fact that the other attribute was deprecated only recently.
| RPSTime | RPSDateTime | Freq | Perc |
|---|---|---|---|
| TRUE | FALSE | 2030 | 59 % |
| TRUE | TRUE | 1192 | 35 % |
| FALSE | FALSE | 210 | 6 % |
| FALSE | TRUE | 1 | 0 % |
Following objects were created:
DRO only Radiopharmaceutical Start Datetime, no Radiopharmaceutical Start time
Possible issues:
DRO only Radiopharmaceutical Start Time, no Radiopharmaceutical Start Datetime
Possible issues:
DRO over midnight (started before midnight, ended after midnight, only Radiopharmaceutical Start Time provided)
Possible issues:
tbd
In the SUV conversion, it has to be accounted for different tracers – i.e., different radionuclide half-lifes, stored in the attribute RadionuclideHalfLife (0018,1075) in seconds. Alternatively, e.g., in case of missing value, the half-life can be determined based on RadionuclideCodeSequence (0054,0300) that stores the radionuclide codes.
All series had the Radionuclide half-life provided. Most series used Fluorine‑18 (F-18) as radionuclide (Table 10).
| RadionuclideHalfLife (s) | Freq | Perc | Corresponds to |
|---|---|---|---|
| 598 | 13 | 0 % | N-13 |
| 1223 | 2 | 0 % | C-11 |
| 4057 | 20 | 1 % | Ga-68 |
| 6586 | 1247 | 36 % | F-18 |
| 6588 | 2081 | 61 % | F-18 |
| 23400000 | 65 | 2 % | Ge-68 |
To check that these attributes are taken into account when SUV is computed, following DROs were constructed:
DRO with Ga-68 as radionuclide, half-life provided
Possible issues:
tbd
In the past, efforts have been made to standardize SUV computation, most notably by the Quantitative Imaging Biomarkers Alliance (QIBA). Furthermore, digital reference objects for SUV computation have been developed; however, these only evaluate the most common scenario with Units = BQML and DecayCorrection = START.
The present manual, together with the extended set of DROs, broadens the scope to cover multiple acquisition and metadata scenarios and can therefore support consistent and reproducible implementation of SUV conversion across software platforms and institutions – an aspect that is particularly critical in multi-center studies.
A limitation of this work that it solely focuses on the body-weight normalized SUV (SUVbw). Other commonly used SUV normalizations, such as SUVlbm, SUVbsa, and SUVibw are not explicitly addressed; however, these can be computed analogously by replacing body weight with the corresponding normalization factors described above.
…
| DICOMTag | Attribute | Vendor-specific |
|---|---|---|
| 0008,0021 | SeriesDate | No |
| 0008,0022 | AcquisitionDate | No |
| 0008,002A | AcquisitionDateTime | No |
| 0008,0031 | SeriesTime | No |
| 0008,0032 | AcquisitionTime | No |
| 0008,0060 | Modality | No |
| 0008,0070 | Manufacturer | No |
| 0008,103E | SeriesDescription | No |
| 0008,1090 | ManufacturerModelName | No |
| 0009,100D | GEDecayCorrectionDateTime | GE |
| 0009,103B | GEAdministrationDateTime | GE |
| 0010,0010 | PatientName | No |
| 0010,0020 | PatientID | No |
| 0010,0040 | PatientSex | No |
| 0010,1020 | PatientSize | No |
| 0010,1030 | PatientWeight | No |
| 0018,1072 | RadiopharmaceuticalStartTime | No |
| 0018,1074 | RadionuclideTotalDose | No |
| 0018,1075 | RadiotracerHalfLifeTime | No |
| 0018,1078 | RadiopharmaceuticalStartDateTime | No |
| 0018,1242 | ActualFrameDuration | No |
| 0018,9701 | DecayCorrectionDateTime | No |
| 0028,1052 | RescaleIntercept | No |
| 0028,1053 | RescaleSlope | No |
| 0054,0300 | RadionuclideCodeSequence | No |
| 0054,1000 | SeriesType | No |
| 0054,1001 | Units | No |
| 0054,1006 | SUVType | No |
| 0054,1102 | DecayCorrection | No |
| 0054,1300 | FrameReferenceTime | No |
| 0054,1321 | DecayFactor | No |
| 0054,1322 | DoseCalibrationFactor | No |
| 0071,1022 | SiemensDecayCorrectionDateTime | Siemens |
| 7053,1000 | PhilipsSUVScaleFactor | Philips |
| 7053,1009 | PhilipsActivityConcentrationScaleFactor | Philips |